Artificial intelligence with temporal features outperforms machine learning in predicting diabetes.

ABSTRACT: Diabetes mellitus type 2 is increasingly being called a modern preventable pandemic, as even with excellent available treatments, the rate of complications of diabetes is rapidly increasing. Predicting diabetes and identifying it in its early stages could make it easier to prevent, allowing enough time to implement therapies before it gets out of control. Leveraging longitudinal electronic medical record (EMR) data with deep learning has great potential for diabetes prediction. This paper examines the predictive competency of deep learning models in contrast to state-of-the-art machine learning models to incorporate the time dimension of risk. The proposed research investigates a variety of deep learning models and features for predicting diabetes. Model performance was appraised and compa

SUBMITTER: Naveed I 

PROVIDER: S-EPMC10599553 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature